Design of PSO Based Optimization Fuzzy Logic-MPPT Controller to Improve Performance of PV System

Solar energy is clean and abundantly available. It is nowadays a potential solution to reduce greenhouse gas emissions and is the most appropriate for the production of electricity from renewable sources. In the p–v curve of the photovoltaic system (PV), there is a point called Maximum Power Point (MPP), and this point plays a very important role in obtaining the maximum power of a solar panel as it allows an optimal use of a photovoltaic system, regardless of climatic conditions. In this paper, the authors develop an advanced control system combining the concepts of Fuzzy Logic (FL) and Particle Swarm Optimization (PSO) to track the Maximum Power Point (MPP) in a Photovoltaic (PV) system. Using innovative tuning procedures, the parameters of the adopted fuzzy logic controller have been optimized by particle swarm optimization, in order to find the optimum membership function MFs and scaling factors of a fuzzy system with the aim to achieving the accurate and desired results. The synthesized PSO optimized FLC (PSO-FLC) is implemented and the simulation results of selected control approach show the good tracking and rapid response to change in different varying atmospheric conditions.